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Python Data Analysis

You're reading from   Python Data Analysis Perform data collection, data processing, wrangling, visualization, and model building using Python

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Product type Paperback
Published in Feb 2021
Publisher Packt
ISBN-13 9781789955248
Length 478 pages
Edition 3rd Edition
Languages
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Authors (2):
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Ivan Idris Ivan Idris
Author Profile Icon Ivan Idris
Ivan Idris
Avinash Navlani Avinash Navlani
Author Profile Icon Avinash Navlani
Avinash Navlani
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Toc

Table of Contents (20) Chapters Close

Preface 1. Section 1: Foundation for Data Analysis
2. Getting Started with Python Libraries FREE CHAPTER 3. NumPy and pandas 4. Statistics 5. Linear Algebra 6. Section 2: Exploratory Data Analysis and Data Cleaning
7. Data Visualization 8. Retrieving, Processing, and Storing Data 9. Cleaning Messy Data 10. Signal Processing and Time Series 11. Section 3: Deep Dive into Machine Learning
12. Supervised Learning - Regression Analysis 13. Supervised Learning - Classification Techniques 14. Unsupervised Learning - PCA and Clustering 15. Section 4: NLP, Image Analytics, and Parallel Computing
16. Analyzing Textual Data 17. Analyzing Image Data 18. Parallel Computing Using Dask 19. Other Books You May Enjoy

Stemming and lemmatization

Stemming is another step in text analysis for normalization at the language level. The stemming process replaces a word with its root word. It chops off the prefixes and suffixes. For example, the word connect is the root word for connecting, connected, and connection. All the mentioned words have a common root: connect. Such differences between word spellings make it difficult to analyze text data.

Lemmatization is another type of lexicon normalization, which converts a word into its root word. It is closely related to stemming. The main difference is that lemmatization considers the context of the word while normalization is performed, but stemmer doesn't consider the contextual knowledge of the word. Lemmatization is more sophisticated than a stemmer. For example, the word "geese" lemmatizes as "goose." Lemmatization reduces words to their valid lemma using a dictionary. Lemmatization considers the part of speech near the words for...

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